Publication activity
Articles grouped by publication year
Hover over a year or focus the chart and use arrow keys to inspect values.
2026 is year to date. 0 undated publications excluded.
Research across participating journals · All insights follow your collection filters.
Publication activity alongside incoming citations.
Articles grouped by publication year
Hover over a year or focus the chart and use arrow keys to inspect values.
2026 is year to date. 0 undated publications excluded.
OpenAlex · year of the citing work
Hover over a year or focus the chart and use arrow keys to inspect values.
2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.
Leading affiliations and themes in this collection.
Full distributions & methodology ↓Independent sources. Clear time scales.
Crossref and OpenAlex · separate totals for the same publication cohorts
Hover over a year or focus the chart and use arrow keys to inspect values.
Latest lifetime totals, grouped by the cited article’s year. These are not citations received in that year.
OpenAlex · incoming citation links grouped by citing-work year
Hover over a year or focus the chart and use arrow keys to inspect values.
2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.
Select journals to compare the same collection filters. Source totals stay separate. These measures describe research activity, not journal quality.
Articles by publication year
Latest lifetime totals · grouped by publication year
Latest lifetime totals · grouped by publication year
By year of the citing work · 2017–2026
2026 is year to date. Crossref and OpenAlex lifetime charts share a citation scale. Unknown observations appear as gaps; known zero stays zero. Annual receipts use available OpenAlex histories and may not sum to lifetime totals. 0 undated publications excluded from publication-year charts.
Crossref citation coverage: 610 / 610 publications (100.0%). Latest observation: 21 Oct 2026, 07:22 UTC. Means and percentages use records with known counts.
DOI-matched OpenAlex observations for the same selected publications. These counts are separate from Crossref and are never added together.
Observation range: 21 Oct 2026 07:22 UTC — 22 Oct 2026 16:23 UTC. Missing matches are not zero citations. Previous observations may remain if a refresh fails or a DOI no longer matches.
OpenAlex affiliations and primary-topic classification. Each publication counts once per institution or country; multi-affiliated publications appear in multiple groups, so percentages can sum above 100%. Countries describe author affiliations, not nationality. Topics use one primary topic per publication.
595 / 610 with data · 15 missing or unmatched. Percentages use all 610 selected publications.
595 / 610 with data · 15 missing or unmatched. Percentages use all 610 selected publications.
610 / 610 with data · 0 missing or unmatched. Percentages use all 610 selected publications.
Citations are the latest recorded totals for articles published in each year, not citations received during that year. Crossref and OpenAlex remain separate and share the same citation scale. 2026 is incomplete; newer articles have had less time to receive citations.
0 undated publications excluded. Unknown citation counts are shown as —, never as zero. Partial coverage can understate totals; expand each table for known / total records.
| Publication year | Journal / scope | Publications | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2024 | All selected publications | 610 | 610 | 610/610 | 610/610 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2024 | All selected publications | 853 | 610 | 610/610 | 610/610 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2024 | All selected publications | 995 | 610 | 610/610 | 610/610 |
Incoming citations to the selected publications, grouped by the year of the citing work. This is separate from lifetime citation totals grouped by the cited article’s publication year.
The publication filters above define which articles receive the citations. The citation-year range below only controls this chart and the incoming-citation comparison. Removing publication-year filters includes older articles’ incoming citations too.
Annual history available for 610 / 610 selected publications. Supported display window: 2017–2026; 2026 is incomplete. Within a successfully fetched ten-year window, omitted years mean zero. Missing histories and years beyond a saved observation’s window remain unknown (—); partial coverage can understate totals.
Annual-history observations (UTC): 2026-10-21T07:22:53.425590+00:00 — 2026-10-22T16:23:48.910397+00:00. Older observations may be retained after failed or incomplete refreshes.
| Citation year | Journal / scope | OpenAlex · Citations received by year | Publications | Annual history known |
|---|---|---|---|---|
| 2017 | All selected publications | 1 | 610 | 610/610 |
| 2018 | All selected publications | 0 | 610 | 610/610 |
| 2019 | All selected publications | 0 | 610 | 610/610 |
| 2020 | All selected publications | 0 | 610 | 610/610 |
| 2021 | All selected publications | 1 | 610 | 610/610 |
| 2022 | All selected publications | 0 | 610 | 610/610 |
| 2023 | All selected publications | 1 | 610 | 610/610 |
| 2024 | All selected publications | 130 | 610 | 610/610 |
| 2025 | All selected publications | 448 | 610 | 610/610 |
| 2026 | All selected publications | 414 | 610 | 610/610 |
Counts represent citation links, not unique citing papers across a journal: one paper citing two selected articles contributes two links. Older citations outside this window are excluded, so annual sums need not equal lifetime totals. OpenAlex methodology ↗
Publications by publication year. 2026 is an incomplete year.
| Period | Publications |
|---|---|
| 2024 | 610 |
Latest Crossref totals for the selected publications; not citations received in the selected years.
Unknown counts are excluded from the mean, median and cited-publication rate.
Same filters, source and counting rules across journals. Descriptive statistics, not a quality ranking.
| Journal / publisher | Publications | Crossref citations | OpenAlex citations | OpenAlex coverage | Crossref mean | Crossref median | Crossref cited %* | Crossref coverage |
|---|---|---|---|---|---|---|---|---|
| Bussecon Review of Social Sciences Bussecon International Academy | 11 | 16 | 16 | 11/11 | 1.45 | 1 | 54.5 | 11/11 · 100.0% |
| International Journal of Business Ecosystem & Strategy Bussecon International Academy | 138 | 200 | 227 | 138/138 | 1.45 | 1.0 | 60.1 | 138/138 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 32 | 44 | 49 | 32/32 | 1.38 | 0.0 | 46.9 | 32/32 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 429 | 593 | 703 | 429/429 | 1.38 | 1 | 57.3 | 429/429 · 100.0% |
* Percentage among publications with a known citation count.
This study aims to investigate the effect of employee motivation and employee engagement mediated by job satisfaction on job performance. This study employs explanatory research with a quantitative approach. The population in this study consisted of all employees of retail company X. The sampling technique used was saturated sampling, and the number of research samples was 150. Data was collected through surveys and documentation, and the instrument was tested using Likert scales. The data was analysed using Structural Equation Model Partial Least Squares (SEM-PLS) modelling. The results of this study indicate that employee motivation can increase job performance, while employee engagement cannot increase job performance. Furthermore, the findings revealed that employee motivation can increase job satisfaction while employee engagement cannot. Job satisfaction can increase job performance. Job satisfaction can mediate the effect of employee motivation on job performance, but it cannot mediate the effect of employee engagement on job performance. According to the findings of this study, Company X should be able to provide motivational stimulus to employees by increasing salaries and work incentives, as well as increasing training and developing employee skills, so that workers can work effectively and efficiently.
This study presents a systematic literature review analysing the impact of artificial intelligence (AI) on higher education, focusing on its methods, results, and implications. By synthesising a diverse range of academic papers, the review explores how AI technologies influence educational standards and practices in higher education institutions. Findings reveal that AI has the potential to enhance the quality of higher education by diversifying teaching responsibilities, customising learning experiences, and employing intelligent, adaptive teaching strategies. These capabilities position AI as a transformative tool for improving educational delivery and outcomes. However, the study also highlights significant challenges associated with integrating AI into higher education. These challenges include delineating the appropriate scope of AI use, addressing inequalities in access to digital resources, and ensuring adequate training and support for educators and students. The review underscores the importance of understanding these complexities to guide the development of effective strategies and policies that optimise AI's potential while mitigating its limitations. The review offers critical insights into the dual role of AI in higher education, where it can either advance or hinder educational standards depending on how it is implemented. By examining the advantages, limitations, and broader consequences of AI-powered instructional tools, this study provides a comprehensive perspective on the intricate relationship between AI and educational quality. The findings aim to inform educators, policymakers, and stakeholders about the opportunities and challenges of adopting AI in higher education, contributing to the development of inclusive, innovative, and sustainable educational practices.
The utilization of powerful machine learning models in artificial intelligence offers novel prospects for the identification of fraudulent activities. Artificial Intelligence (AI) is a revolutionary technological tool that enhances the ability to detect and prevent fraud by improving efficiency and effectiveness. This research offers a thorough examination of the utilization of artificial intelligence technology in the realm of procurement fraud prevention and detection. Additionally, it highlights the obstacles that arise when employing machine learning techniques for the purpose of identifying and preventing fraudulent activities. A mixed methods approach was employed in this study, wherein data was collected through an unstructured interview and questionnaire. We conducted a comprehensive review of relevant scholarly articles and online resources. The findings indicate that fraudsters are progressively advancing in their skills, which poses a significant challenge in detecting fraudulent activities. The advent of AI in fraud detection has demonstrated its transformative impact. AI has achieved unparalleled precision and velocity in crime detection and prevention, surpassing the capabilities of any human. Artificial intelligence (AI) enhances the capacity for automation. Accessing unstructured data in the form of spreadsheets, digital documents, and email inboxes poses a significant issue for the procurement function. In order to achieve a successful procurement transformation, businesses should prioritize the creation of essential tools, guarantee acceptance through the establishment of a superior user experience, and integrate both novel and pre-existing technology. It is imperative to disseminate knowledge to the general public regarding the escalating sophistication of artificial intelligence (AI) in the realm of fraud detection and prevention. This includes elucidating the potential benefits of AI in identifying patterns of suspicious activities, assessing its efficacy in predicting potential threats or fraudulent activities prior to their manifestation, and exploring its utility in analyzing historical data pertaining to both familiar and unfamiliar forms of fraudulent behavior.
Financial inclusion, especially the adoption of fintech, has emerged as a crucial avenue for removing the financial access divides in developing countries, including Bangladesh. Following the comprehensive analysis, this article intends to outline Bangladesh's recent experiences with fintech-based financial inclusion, identify the short-comings and hence make policy suggestions. Being a descriptive research, cross-sectional and observational research approaches are applied for the explanatory analysis of secondary data. Results suggest an urban-rural gap in the implementation of digital financial services, with urban areas consistently having higher rates of fully online branches and a greater number of financial machines. Despite this, the sharp rise in the issuance of active cards is a positive sign suggesting an expansion of consumer base and an adoption of electronic modes of payment. Moreover, inter-bank electronic fund transfers and online banking have experienced increasing uptake, revealing a progressing trend towards digital transactions within the banking industry. Additionally, the study identifies a speedy growth in the number of mobile financial services accounts in both urban and rural areas. This study adds to the exchange of ideas regarding financial inclusion by carrying out a detailed study of Bangladesh's digital financial transformation, exemplifying the accomplishments, obstacles, and future research directions. It highlights the need for targeted policies and ongoing research efforts to build inclusive financial systems to serve the entire society’s interest. Nevertheless, the observations will have both theoretical and practical significance, contributing towards building capability in harnessing technology for sustainability, community uplifting, and shaping a brighter future.
The 21st century has witnessed a rapid surge in industrial pollution, accompanied by the depletion of natural resources, prompting a collective call to action. As a result, the greening of corporations and ecological sustainability has emerged as a matter of paramount importance for decision-makers worldwide. This study, thereby, aims to examine the implementation of environmentally responsible (Green) human resource management practices in the health sector and their influence on organizational sustainability performance. Methodologically, a descriptive approach was employed, utilizing a questionnaire survey to collect data from 250 healthcare employees within Pakistan's healthcare sector. The study's statistical outcomes indicate that green hiring positively influences economic performance but not social and environmental performance. However, green training, involvement, performance management, and compensation are all positively related to organizational sustainability performance, encompassing social, economic, and environmental aspects in Pakistan’s healthcare sector. By summing up, this study concludes the significance of customizing green HR practices for enhancing sustainability performance in the healthcare sector. It underscores the crucial role played by green human resource management practices and their impact on organizational sustainability performance in a developing country context, specifically in Pakistan.
As access to healthcare has come under increasing scrutiny, patient waiting times have become crucial. Qualitative research provides an in-depth understanding and reflections of the nurses at Nthabiseng Clinic in Capricorn region, Limpopo Province, South Africa.This article is based on an investigation of patient waiting, which used in-depth semi-structured interviews with five strategically selected healthcare professionals to disentangle the web of different elements that can affect the length of time a patient might wait at the hospital. We identified two superordinate themes that emerged from our thematic analysis. The data analysis identified two key themes that influenced how patient waiting time was related to patients and operational matters during clinic visits: 1) Determinants of patient waiting time at a clinic visit: (i.e. a lack of definitions of patient waiting time; patient waiting time contributing factors; patient waiting time seen through patients; operational challenges regarding patient waiting time); as well as 2) Patient waiting time policy position (i.e. South Africa’s patient waiting time specific policy/ies and/or legislative framework; A clinic’s specific development plan; DOH’s assistance to a clinic). As healthcare systems strive to enhance accessibility and patient experience, this study offers invaluable insights into the multifaceted nature of patient waiting times, paving the way for evidence-based strategies to address this critical issue.
This study employed a conceptual framework to elucidate the issue of incivility. The researcher created a cohesive conceptual framework to facilitate the construction of knowledge and to offer a rational elucidation of the knowledge acquired during this study. This will provide a framework for a deeper comprehension of incivility in professional nursing education in South Africa. A qualitative exploratory descriptive methodology was employed. The research was conducted in a nursing college in partnership with a university of technology and a university-affiliated nursing school. A selected sample of fifteen (15) students and ten (10) nurse educators was utilised for data collection. Semi-structured, in-person interviews were used to gather data until saturation was achieved with 23 participants. Participation was voluntary, and discussions were kept confidential. Distinct themes arose from the data analysis and were interpreted through interpersonal relations theory. The related notions were delineated as Part 1 – the leaves of the tree: manifestations of incivility, Part 2 – the trunk of the tree: incivility itself, and Part 3 – the roots of the tree: the origins of incivility within the framework of incivility.
Backyard gardening holds immense promise as a viable solution to combat the escalating rates of hunger and poverty in South Africa. This study examines the dynamics of backyard gardening, its significance, potential contributions to food security and the myriad challenges it faces. The literature review explores the diverse dimensions of backyard gardening drawing insights from scholarly research and policy documents. The study underscores the pivotal role of backyard gardening in addressing food security, enhancing nutrition and promoting socio-economic resilience within communities. However, significant barriers such as limited access to land, water scarcity and inadequate support structures pose formidable challenges to its widespread adoption and effectiveness. Analysing the legislative frameworks, policy landscape and organisational initiatives surrounding backyard gardening illuminates’ pathways for overcoming barriers and harnessing its transformative potential. Moreover, it underscores the importance of reimagining backyard gardening as a dynamic strategy for inclusive development, grounded in principles of equity, sustainability and community empowerment. Through strategic interventions aimed at promoting equitable land tenure, enhancing water resource management and fostering community capacity building, South Africa can leverage backyard gardening as a powerful tool in its quest for a more resilient and food-secure future.
This systematic review examines the initiatives and challenges faced by the South African government in promoting indigenous languages following the end of apartheid. This study evaluates progress, identifies barriers, and offers recommendations for future policy and practice. A systematic literature review approach was utilised to analyse government policies and initiatives aimed at promoting indigenous languages from 1994 to 2024. Searches conducted in electronic databases utilised terms such as "South Africa indigenous languages." The inclusion criteria included peer-reviewed articles, government reports, and policy documents that concentrate on language revitalisation initiatives. Findings reveal ongoing challenges stemming from historical marginalisation and systemic obstacles associated with colonial and apartheid-era policies. Indigenous languages, despite being constitutionally recognised, encounter significant implementation gaps, resource limitations, and societal attitudes that impede their incorporation into education, governance, and media. Recommendations emphasise the importance of improved policy implementation via augmented funding, initiatives for educational capacity-building, and the promotion of indigenous languages in media and public discourse. Addressing negative societal attitudes and promoting cultural pride is crucial for fostering linguistic inclusivity and preserving the diverse linguistic heritage of South Africa.
This article reports on literature review and the reflective practice of teachers and school principals on the use of action research in identifying teachers’ professional development (TPD) needs required for a successful implementation of blended and virtual learning. This article sought to contribute to the body of knowledge of teachers’ needs analysis and development; teachers’ digital competencies; and action research to the field of education. School principals and teachers who participated in this study confirmed that action research is an effective strategy that can be used in TPD. They further stressed that action research can be used to replace the existing ‘one size fits all strategy’ that is currently used blatantly across highly adequately and under-resourced schools. Using action research helped them expose realities entrenched within teaching and learning in less privileged schools. This study recommends the use of action research as strategy for identification of teachers’ and learners’ needs that should inform the contents and nature of teachers’ professional development programs.
Source coverage refers to this result set; a publication may occur in several sources. Sync times refer to contributing journals.
Missing abstracts: 0 · Missing authors: 0 · Missing publication dates: 0 · Dates without day precision: 0
| Source | Most recent successful journal sync | Latest attempt |
|---|---|---|
| crossref | 21 Oct 2026 07:22 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |
| ojs-rest | 21 Oct 2026 07:22 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 06:46 UTC |
| oai-pmh | 20 Oct 2026 19:56 UTC · ijfbs | complete · ijfbs · 20 Oct 2026 19:55 UTC |
| openalex-enrichment | 21 Oct 2026 07:23 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |